Machine Learning Zoomcamp: Free ML Engineering course. Register here!

DataTalks.Club

Articles Slack Events Podcast Books Courses

DataTalks.Club Anniversary Podcast

Season 19, episode 3 of the DataTalks.Club podcast with Alexey Grigorev

Did you like this episode? Check other episodes of the podcast, and register for new events.

Transcript

The transcripts are edited for clarity, sometimes with AI. If you notice any incorrect information, let us know.

DataTalks.Club anniversary "Ask Me Anything" event with Alexey Grigorev

Alexey: Hi, everyone. Welcome to our event. This event is brought to you by DataTalks.Club, a community for people who love data. We have weekly events, but today is a special one because this is not our usual Thursday event. Today is our anniversary "Ask Me Anything" podcast, and Johanna will be asking me questions a bit later. Right now, I’ll just go through our usual slides. DataTalks.Club has turned four, so thank you all for being with us, and a special thanks to Johanna for being part of the podcast for so long. It’s really amazing. (0.0)

Alexey: If you want to know more about our events, there’s a link in the description. Click on that and don't forget to subscribe to our YouTube channel. We’re close to reaching 50k subscribers, and I’m really excited about that. Also, join our Slack community where you can hang out with other data enthusiasts. During today's interview, you can ask any questions. Since this is an "Ask Me Anything," please feel free to send your questions. The more, the better! There's a link in the live chat. If it's not pinned yet, I’ll make sure it is. Click on the link and ask away! (0.0)

Alexey: Today, we have a special host, Johanna, who is the mastermind behind all of the podcast episodes. I know you’ve been doing this for almost three years. (0.0)

Johanna: Yeah, almost three years now, maybe around 2.5. I thought about it recently. And fun fact, I just got my official DataTalks.Club email address. I’m officially "in" now! (1:35)

Johanna: So, welcome everyone! I see some familiar faces on YouTube. The idea for this podcast is similar to what we did last year. We’re turning the tables, and Alexey will be in the guest seat this time. I’ll give you all the opportunity to ask him questions. But first, I’ll ask the guest to introduce himself — just keep it short, please! (1:35)

The founding of DataTalks.Club

Alexey: Hi, everyone. My name is Alexey, or Alexei. In Russian, it's actually "Alexei," but when I was in the U.S. for the first time, people started calling me Alexey, and I got used to it. You can call me whatever you want. I started DataTalks.Club four years ago by accident. I remember it was September 19, 2020, when everyone thought COVID was over, but it wasn’t. That summer, we all relaxed, thinking we could travel again. I remember going to the seaside in Germany, but by September, restrictions were back, and we were stuck at home. That’s when I thought, “Maybe I should start something.” And that’s how DataTalks.Club began. (2:29)

Alexey: It's been four years now, and I’m really grateful to everyone who’s been involved. I’ve talked to so many amazing people over the years. I didn’t prepare for this introduction, so I’m not sure what else to say! (2:29)

Alexey's transition from Java work to DataTalks.Club

Johanna: That’s great! Most people probably know you anyway. Before DataTalks.Club, you were doing mostly Java work, right? And now you’re full-time with DataTalks.Club? (3:52)

Alexey: Yes, I was a data scientist at Helix. In April 2023, more than a year ago, I decided to focus on just one thing: DataTalks.Club. Before that, I was essentially doing two full-time jobs — both demanding jobs that required a lot of attention. It became impossible to give both the time they deserved. So, I decided to focus on DataTalks.Club, especially since it had become profitable. I did the math and figured out that the income from DataTalks.Club would be enough to cover living costs in Berlin, which, to be honest, isn’t cheap! (4:06)

Johanna: Yeah, Berlin definitely hasn’t gotten any cheaper! (4:53)

Alexey: Exactly. It’s only getting more expensive. (4:57)

Growth and success of DataTalks.Club courses

Johanna: So, how has the year been for you since we last talked? (4:58)

Alexey: It’s been a really good year. We got two new sponsors, and our courses are doing well. Our Data Engineering course, in particular, has been very successful. Maybe I should give some background on the courses. We currently have five: Machine Learning Zoomcamp, Data Engineering Zoomcamp, and MLOps Zoomcamp were the ones we talked about last time. Since then, we’ve added two more: one on large language models (LLMs) and another on stock market analytics. (5:07)

Alexey: The Data Engineering Zoomcamp has grown unexpectedly popular. We almost don’t promote it — people just recommend it to each other. It’s our most popular course, with 24,000 registrations! For comparison, our machine learning course has 8,000 registrations, which is already a big number. It’s been amazing to see how the course has taken off. (5:07)

Alexey: We also launched the LLM course because, well, everyone was asking for it. And the stock market analytics course was a bit different for us since we usually focus on engineering topics. But it was still well received, and it was interesting because I wasn’t involved in teaching it. Ivan, the lead instructor, took full control. That was a new experiment for us — running a course without my direct involvement — and it worked well. (5:07)

Alexey: So, those were the big highlights this year. (5:07)

Johanna: Yeah, regarding the non-promotion, I think the courses are set up in a way that encourages people to talk about them. People are basically promoting the courses for you! (8:13)

Alexey: Yeah, even outside of the cohorts. For example, when someone on Reddit asks for a data engineering course recommendation, people suggest ours. They’re not even getting any incentives for that — unlike during the course when we give out virtual points. It’s really cool to see that happening organically. (8:30)

Johanna: Yeah, it’s great! So, what’s been the most surprising or fun thing you’ve learned this year while running the community? Anything come to mind? Last year, we talked about people trying to date each other in the community. (8:58)

Alexey: Haha, yeah, that was funny. Maybe it’s still happening, but I don’t hear about it much anymore. What I have noticed is an increase in scams lately. For example, there’s something called the "Upwork scam." People will message you, asking you to create an Upwork account so they can use it to work on your behalf. They offer to split the earnings with you, but this is illegal and can have serious consequences. (9:22)

Alexey: Many communities are dealing with this issue, so if you receive a suspicious message, please report it. And if someone randomly DMs you in the community, that’s usually a red flag. We encourage people to use public channels unless there’s a valid reason for a direct message. If someone is trying to promote something or is asking for your Upwork account, definitely let us know. (9:22)

Alexey: Of course, if someone is asking you out on a date... well, maybe use your judgment! But remember, this is a professional community, not a dating site. (9:22)

Johanna: Yeah, I didn’t know about the Upwork scam. That’s really good to know. Alright, let’s take some questions from the community. Here’s one: "Why did you decide to create a free-to-learn community? What keeps you motivated, and have you ever thought about stopping or leaving the community?" (11:34)

Motivation behind creating a free-to-learn community

Johanna: This one question? Well, luckily I have it open in front of me too. So, why did you choose to create a free-to-learn community? (12:04)

Johanna: Alexey (12:04)

Johanna: There are many reasons, but one of them is that I benefited a lot from free courses when I was starting my career in data science. So, this is my way of giving back to the community. Coursera, for example, used to have free courses — I'm not sure if they do anymore. Apart from Coursera, I was part of a community called Open Data Science, which was a Russian-speaking community based in Moscow. It doesn’t exist anymore because most of the workspaces in Russia have closed. (12:04)

Johanna: Surprisingly, though, many people still associate with this community. For example, there’s a Telegram group called ODS Berlin, one in Munich, and one in Paris. Even though the community itself doesn't exist, it fragmented and decentralized, which is a good example of a real community where things happen organically. Even after the community stopped existing, people continued to self-organize and do more. (12:04)

Johanna: Open Data Science ran a course called ML course, which was a community effort. Around five or six people came together to create it, and it was free. I loved the idea of openness and offering free learning. That course was amazing. It inspired me to do something similar, but in English. When I had the chance, I finally decided to do this and created the Machine Learning Zoomcamp. That course was successful, but it was just me as the instructor, which made it hard. (12:04)

Johanna: One of the students from that course, Ankush, reached out and suggested creating a data engineering course. Together with two other community members, Sejal and Victoria, we put together a course, with each of us covering one or two modules. It was very similar to the ML course. The idea was to offer it for free from the start, and it has grown to be much bigger than I expected. (12:04)

Johanna: What keeps me going is the feedback I get from the community. I believe in free education, and it’s really motivating when people from countries like Nigeria ask if they can complete the course on a tablet. The answer is yes! Knowing that we’re providing education to people who can’t afford paid courses is inspiring. (12:04)

Johanna: That’s true. (16:25)

Alexey: Yeah. And when someone tells me that my course changed their life, that’s the best part. Some people find jobs afterward and send me a message about how their life has changed. One student even decided to donate to DataTalks.Club after getting a job with a training budget. (16:27)

Alexey: Johanna (16:27)

Alexey: That’s so cool. (16:27)

Alexey: Alexey (16:27)

Alexey: Yeah, it wasn’t a lot compared to what sponsors give us — 500 euros — but it felt so much more meaningful. The sad part is that we had to pay taxes, so half of it went to taxes, but that’s life in Germany. (16:27)

Alexey: Johanna (16:27)

Alexey: Yeah, taxes! But you’ve got such a huge community now, with around 100,000 people signed up for your newsletter. That’s insane! (16:27)

Alexey: There was a question about whether I’ve ever thought about stopping. It might happen. When I left my previous job to focus on DataTalks.Club, it coincided with the recession, and many sponsors canceled. I was expecting a certain amount of money, but sponsors pulled out, cutting their marketing budgets. (17:56)

Alexey: At one point, I was losing two or three thousand euros a month after leaving my job. It made me wonder if I made the right decision. Thankfully, it worked out, but I never know what will happen. If the money stops coming in, I’ll have to find another way to earn, which would mean I couldn’t focus entirely on the community. Having two jobs, like when I worked at OLX, was tough. (17:56)

Alexey: Today, I had two calls with potential sponsors. Sometimes, I think it's going well, but then they stop replying. But right now, I’m optimistic. We have enough runway for the rest of the year and a bit of next year. The Data Engineering Zoomcamp will continue, and we might even start a new course. (17:56)

Johanna: Wow. You also mentioned taxes. You had to pay a lot of taxes in advance? (20:14)

Johanna: Alexey (20:14)

Johanna: Yes, in Germany, we have this concept of prepaid taxes. The tax office calculates your expected income based on the first few months of the year. What happened to me last year is they took my income from the first three months, multiplied it by four, and told me to pay 50% of that each quarter. But it wasn’t accurately calculated. (20:14)

Johanna: The tax office was basically taking all the money I earned. They canceled the last quarter payment, and in the end, they even refunded some money because they had been overly optimistic in their calculations. This year isn’t as bad since they used last year’s profit for their estimate, but it’s still frustrating to wake up and see that half your money is gone because of taxes. I gave them permission to take the money automatically to avoid forgetting to pay, but it’s tough. (20:14)

Johanna: Yeah, taxes are so much fun! (22:11)

Alexey: In Germany, it may not be the best place for business, but I see where the taxes go. The roads are maintained, my child attends school for free, and the food there is organic and free as well. I received an education in Germany for about 300 per semester. (22:13)

Alexey: With the influx of Ukrainians in Germany, the country has invested significantly in upskilling them. Many who arrived two years ago are now working and contributing back to the government through taxes. (22:48)

Alexey: I'm pleased to see that this money is not just going into someone's pockets but is being reinvested into society. I may not know the whole story, but from what I observe, I am happy. (22:48)

Alexey: I don't want to delve too much into politics, but the current situation in Germany appears promising. (22:48)

Johanna: But that's the state of the world at the moment. Can we return to some of the questions? One is: Are you still active in machine learning or data science, working on projects aside from the course? How do you stay relevant and up to date? (23:38)

Staying updated in data science through pet projects

Alexey: That's a good question. It's quite challenging. I have pet projects, which is how I try to stay updated. However, pet projects are not the same as working on real products. I still acquire some skills, but it's different from when I worked at Alix, where my fraud detection system was used on millions of items daily. (24:03)

Alexey: It's nowhere close to that level, but I still do my best. One recent pet project involved generating horror stories. My son loves horror stories and often asks me to tell him one about something random, like a tree or a construction site. (24:03)

Alexey: It’s tough to come up with so many horror stories on the spot. So, I decided to take a picture of whatever he pointed to, input it into GPT, and have it generate a horror story. The results were incredibly good. The stories were so impressive that I thought it would be a shame to keep them on my phone. (24:03)

Alexey: Initially, I put the stories on a small GitHub Pages website. Then, I thought it would be nice to have illustrations for them. I used DALL·E to generate the illustrations, and I even implemented text-to-speech functionality. Instead of reading the stories myself, a voice could narrate them. (24:03)

Alexey: Eventually, I automated the entire process. I take a picture, upload it to an S3 bucket, and I can upload as many pictures as I want. Periodically, a GitHub Action pulls one of the images, creates a story based on it, generates an illustration, produces an audio file, and publishes it as a podcast. (24:03)

Hosting a second podcast and maintaining programming skills

Johanna: Wow, that's amazing. So, you're basically hosting a second podcast now. (26:37)

Alexey: Let's see how popular it becomes. Maybe I'll stop working with people. But all of this is open source; you can find it on my GitHub. Even though the content is in Russian, the code is in Python, so don't worry. (26:43)

Alexey: I try to do things like that to stay updated. For example, the LM course required some preparation and research. I also created an example project about gym exercises. If someone wanted to replace a specific exercise, they could chat with the system and ask for a suitable alternative. (26:43)

Alexey: That was another cool project. I also try to maintain my programming skills by working on various things, from simple automation scripts to larger projects. For instance, we currently have a course management platform written in Django. While it doesn't involve AI or machine learning, I spend time on it to keep my coding skills sharp. (26:43)

Alexey: Last year, I was in a managerial role at Alix, and DataTalks.Club wasn’t a place where I wrote code. Over time, I realized my coding skills were not as sharp anymore. Now, I force myself to do different things to remember how to program. (26:43)

Skepticism about LLMs and their relevance

Johanna: That's a common experience for someone who moves up the ladder, right? It happens to everyone. (28:56)

Alexey: Yes, exactly. I was skeptical about the LLM course at first. I thought LLMs were just another trend like Web 3.0 or Blockchain — something everyone talks about for a month, and then it fades away. (29:14)

Alexey: I remember the first time I learned about GPT; someone asked it to write a poem about machine learning during one of our courses. It was actually good, which made me reconsider my skepticism. (29:14)

Alexey: As I saw more about LLMs last year, I thought it was time for us to get involved as well. I didn't work on LLM projects at Alix, but many concepts from my past experience still apply. For example, RAG (retrieval-augmented generation) is a core component of R. I have been working with search technologies for over ten years, so I felt well-prepared to tackle these new developments. (29:14)

Alexey: The course went really well, and I’m happy with the outcome. I also learned many new things. (29:14)

Johanna: Great! I had a similar introduction to LLMs. I tend to trust things only when I understand them. At first, I was skeptical, but after taking a university course on it, I found it super interesting. Transformers are fascinating, and I realized I could experiment with them myself. The course is still available, so people can check it out. (31:08)

Transitioning to DataTalks.Club and personal reflections

Johanna: The next question is, you've been doing DataTalks.Club full-time for almost two years. How's life? Would you reverse your decision to leave corporate work or change anything? (31:53)

Johanna: I think we've partially answered that, but perhaps you can expand. (31:53)

Johanna: Actually, this question comes from a friend of mine. Life has been good; I wouldn't change anything. I have no regrets. There were tough times and incredibly good times, but I am happy with where I am now. (31:50)

Johanna: My only hope is that it continues. Some things are outside of my control, but if I need to find a job for any reason, I’m confident I can at least find a software engineering role where I can be useful. (31:50)

Johanna: I have no regrets about returning to corporate life. If I were to do that, it would likely be with a smaller company. I've also thought about what I would do if not at DataTalks.Club. (31:50)

Johanna: I see myself in a position where I can teach and code, combining both interests. I want to remain technical but also fulfill my passion for educating others. (31:50)

Memorable moments and the first event's success

Johanna: Cool! What was a memorable moment early on when you knew this would take off? (33:32)

Alexey: It was during our first event, which was organized by a different Dimitry. Hi, Dimitry! Someone asked me about it on LinkedIn, and I shared the details in a form. (33:40)

Alexey: When we had our first event, I realized this could be something meaningful. Initially, while working at Alix, I had a clause in my contract stating I couldn't engage in side projects without explicit permission. (33:40)

Alexey: The first couple of months, I operated under the radar. I wasn't dedicating much time to it; I was just setting things up and seeing how they progressed. (33:40)

Alexey: I reached out to participants to understand their interests and goals. This way, I met many people who later became co-instructors, podcast guests, or friends. (33:40)

Alexey: One participant asked where they could speak, and I told him I knew of a suitable venue. Since I understood the audience's interests, his talk was relevant, attracting 100 attendees. (33:40)

Alexey: At that moment, I realized this wasn’t just a side project; it was becoming something significant, prompting me to speak to my manager. (33:40)

Alexey: He approved, and after that first event with 100 participants, I knew I was on to something. (33:40)

Community building during the pandemic

Johanna: The birth of DataTalks coincided with the pandemic, right? Many communities were formed during that time. Why do you think DataTalks is still thriving while many other communities have faded? (36:19)

Alexey: I've consulted with many people about community building. There's a misconception that you can create a community, and it will sustain itself. This can happen, as seen with Open Data Science, which became a true community. Even after their main platform disappeared, the community remained intact. (36:37)

Alexey: However, many communities require active investment of time and effort. You need to keep it alive; otherwise, it will fade away. (36:37)

Alexey: If you don't actively engage with the community, people won't return, leading to its decline. (36:37)

Alexey: I kept DataTalks alive because I gained so much from it. The positive feedback I received was incredibly rewarding, motivating me to continue. Every time someone expresses gratitude, saying the course is beneficial, it encourages me to keep going. (36:37)

AI's impact on data analysts and future roles

Johanna: Okay. What do you think about the possibility of AI replacing data analysts? (38:31)

Johanna: I might have... (38:44)

Alexey: Yeah, you see the question, did you? It's in the archives. In your opinion, (38:47)

Johanna: It's back, right? (38:57)

Johanna: Yeah, let me see. (38:58)

Alexey: Yes. (39:00)

Johanna: What do you think about the possibility of AI replacing data analysts? In your opinion, what could be the next level for a data analyst? An ML engineer? (39:01)

Alexey: I think partly yes, for simple tasks. However, being an analyst involves much more than just using SQL to build dashboards. There's a component of talking to people and business domain expertise. (39:14)

Alexey: You could also argue that AI has replaced data scientists. You don't need an LLM to build a good machine learning model. Five or ten years ago, we had AutoML packages where you just needed to input a CSV file and get a reasonably good model. (39:14)

Alexey: For example, in a Kaggle competition, if you upload a CSV file to Azure AutoML or Google AutoML, you will receive a decent result. Of course, you won't rank in the top ten without three months of work, but it can produce a model ready for production. (39:14)

Alexey: So why are data scientists still around? It indicates that the role involves more than simply taking a CSV file and training a model. (39:14)

Alexey: I don't believe AI will replace data analysts, data scientists, or anyone who needs to use their intellect at work. AI can assist people rather than replace them. It's similar to how autopilot systems were introduced; pilots are still needed. (39:14)

Alexey: Even now, I’m not sure how much involvement pilots have. Perhaps they just sit and watch the flight. Yet, there must be a reason for their continued presence. (39:14)

Alexey: I think the role of data analysts will become simpler. They won’t need to spend so much time writing complex SQL queries. They can delegate tasks like bug finding. (39:14)

Alexey: However, communication with the business is still crucial. Understanding which metrics to compute requires conversations with stakeholders about what matters to them. Metrics don’t just appear; they need to be defined through discussions. (39:14)

Discussion on AI in healthcare

Johanna: Exactly. I'm more from the medical field, and I hear similar ideas about AI replacing doctors. However, people visit doctors for more than just a diagnosis; they want someone to talk to. (42:24)

Alexey: Would people prefer to talk to AI? Maybe it's just a German thing, but sometimes I feel worse after going to a doctor. (42:39)

Johanna: That could actually be an improvement. (42:53)

Alexey: Sometimes, yes. For instance, there was a time when my child started kindergarten and brought home various viruses. I was sick all the time. I asked the doctor what I could do, and he jokingly said to get rid of the kid. (42:57)

Johanna: Well, yeah. (43:23)

Alexey: I think a better recommendation from AI might have been helpful, even if it wouldn’t be as memorable. (43:26)

Johanna: I find it amusing that after years of medical school, that was the doctor's answer. (43:35)

Alexey: Later, he explained his reasoning, saying that children produce more viruses than adults. He noted that this is natural and unavoidable. Apart from “getting rid of the kid,” he advised me to drink less coffee, sleep more, and go to the gym — usual recommendations. (43:50)

Johanna: Yeah. (44:20)

Alexey: To be fair, I mostly needed an excuse not to go to work. (44:24)

Age and reflections on personal milestones

Johanna: That makes sense. I have a question that's not the next one, but I think it’s interesting. You were born in 1989, right? (44:37)

Alexey: Yes, I’ll be 35 this year. (44:52)

Johanna: I was also born in 1989. (45:00)

Alexey: My birthday is in November. (45:04)

Johanna: Then you would be 35. (45:09)

Alexey: Every time I calculate my age, I have to do the math. Now it’s 2024, and I was born in ’89, so I will be 35. (45:15)

Johanna: Cool. (45:28)

Johanna: What is the biggest challenge or learning experience you didn’t expect when scaling the community? We’ve touched upon this, but maybe you can expand. (45:30)

Alexey: The amount of time and effort it would require. Looking back, I'm still unsure why I did it. It gave me meaning during COVID when my work wasn’t fulfilling. (45:44)

Alexey: I was already in a managerial role, and it required a lot of work, often without immediate returns. In the first year, I made around $500, if that, and it took about a year and a half before I saw any real income. (45:44)

Alexey: It took significant effort, and I didn’t initially consider scalability. I focused on what I could do to provide value and keep people engaged in the community. They continued to come back. (45:44)

Alexey: Even before it was profitable, I received an offer from a company interested in acquiring the community. I decided against it because I feared that if it became my job, I’d lose my passion for it. (45:44)

Alexey: I enjoy being independent and not having to follow someone else’s agenda or decisions. (45:44)

Johanna: That’s really cool. I didn’t know that. (47:31)

Alexey: This is the first time I’m talking about it in public. (47:36)

Johanna: I think so. Wow. I had no idea. At the beginning, did you feel lonely in your mission? It can be isolating to create a community. (47:38)

Alexey: It is a bit lonely sometimes. (47:50)

Building communities and personal connections

Johanna: I was thinking more about how few people you know who are also building communities. (47:54)

Alexey: For example, I often communicated with the founders of the ML Ops community. We even had a community mastermind group with someone from Locally Optimistic, a community for data analysts, along with members from other communities. (48:02)

Alexey: Every week or every two weeks, we would meet to discuss different challenges. (48:02)

Alexey: Having a community helped me connect with more people than before. That may be one reason I continued this journey — meeting new people and forming meaningful connections. (48:02)

Alexey: For example, Maggie and Antonio are here. Hi, guys! It’s wonderful to have you and everyone else. Developing these connections has been incredibly rewarding. (48:02)

Alexey: I used to have regular lunches with Mehdi, who isn’t in Berlin anymore. The community provided me with so much, and feeling lonely was not one of them. (48:02)

Johanna: Cool. (49:33)

Future goals for the community and courses

Johanna: Yeah, having a group of people wanting to scale the community is definitely beneficial. What would you like to achieve in the upcoming years? That’s a good question. (49:34)

Alexey: So, I need more sponsors. That’s what I want to do. I’m looking to do more courses. We have this course platform, and I mentioned the one I did in Django. Previously, it was a lot of manual work — lots of Python scripts and Google Forms, which required a lot of effort to run a course. Now, it’s much easier. I can just give access to the admin panel of Django to other instructors without being involved. For example, the stock market analytics course happened without my involvement, thanks to this platform. Now, I can be less involved in the day-to-day operations of courses and focus more on creating them. That’s why we also did the LLM course this year; I finally had time to do something else besides managing the operations behind the courses. I want to create more courses, probably something related to data engineering. It also depends on what people want and what companies want to promote. I want to find an intersection that’s useful for both companies and people. Also, I need to pay for this flat, which isn’t cheap. (49:49)

Community involvement and engagement strategies

Johanna: Yeah, it has to be sustainable, right? (51:18)

Alexey: Exactly. So, is there anything I or others can do to help our community grow and improve? That’s from Dayton, you know Dayton? (51:22)

Johanna: Yeah. (51:36)

Alexey: Well, there are many things you can do. First of all, you can be a guest on the podcast. You can tell your friends about the community, help others in Slack, and participate in our “Project of the Week.” This is a great initiative where we prepare a study plan for the week and follow it. It’s a super cool project, but sadly, it doesn’t always get a lot of traction. We should think about how we can get feedback from the community to get people involved. When there’s a project of the week, it’s a bit disheartening when someone like Adonis, who puts a lot of effort into creating the plan, sees that only one person is participating. I believe many people are involved but not everyone is vocal about it. Maybe it would help if you share your progress, so others feel they’re not doing this alone. (51:38)

Johanna: Yeah, that sounds great. (53:43)

Ideas for competitions and hackathons

Alexey: So, we’ve had competitions before, as part of a long course, and we will have a competition for the ML course too. However, we haven’t had a hackathon yet, and that’s something I’d like to do. If anyone wants to get involved, just let me know. (53:46)

Johanna: Yeah, and I’ll add a shameless plug for the podcast. If you feel like you want to be in the guest chair, reach out. It can be about your job or anything that interests you. Don’t be shy! (54:03)

Inviting guests to the podcast

Alexey: Especially for first-time podcast guests! For those who have been on other podcasts, it might be easier since they’ve already shared their experiences. But it’s also interesting to hear from someone who hasn’t spoken on a podcast yet. Everyone has something to share. When I meet people in real life and we talk over tea or something, it’s always fascinating. I often think, “We should be recording this!” I usually invite them to do a podcast. Not everyone agrees, and I don’t judge anyone. It’s not for everyone, but if you want to be on the podcast, please reach out to us. (54:20)

Johanna: Yeah, please reach out! There’s a question about when the stock market analysis course starts. I think it’s already finished, right? But people can… (55:17)

Course updates and future workshops

Alexey: We talked about this recently. The course will run again next year, but we haven’t decided on a specific date or month yet. We’re aiming for around April. We want to do two workshops before that, covering material that wasn’t addressed in the course. We’re discussing it now. So, you’ll definitely hear about the workshops soon. One is probably in November and another in February. We’ll announce them in our newsletter and on social media, so you won’t miss them. There will also be a form for signing up for the course. (55:29)

Johanna: I participated a little in the last one, and it was really interesting. I’m really into finance, so it was a great experience! (56:19)

Podcast preparation and research process

Alexey: That’s awesome! Now, this is a question from Johanna: how do you prepare the questions for the podcast? How has this evolved over time? (56:27)

Johanna: My qualifying feature for this position was that I commented on a LinkedIn post saying I had listened to all the episodes, which was true. Alexey reached out to me and asked if I wanted to help prepare the episodes almost three years ago. How I usually do it is that I get the guest's information and do a bit of research on their LinkedIn and the material they provide. I kind of stalk the guest a bit and come up with good topics. Then I usually meet with them before the episode to create some questions. They usually review them and agree on what they want to be asked, and then we’re ready to go. It’s a lot of fun because I get to learn about people’s careers and a wide range of topics. It usually takes me about an hour per guest, from start to finish. (56:41)

Alexey: Were you surprised that not all the questions you prepare get asked? (57:48)

Johanna: Yeah, definitely! Alexey has a few backup questions, but I often have to say that especially after meeting the guest, I sometimes don’t listen to the episode again because I feel like I’ve heard everything already. (57:59)

Alexey: So, you’re kind of a podcast host yourself now, right? (58:22)

Johanna: Yeah, I am! I like being behind the scenes, but sometimes it’s fun to talk. (58:25)

Career opportunities in data science and transitioning fields

Johanna: What do we have? Maybe one more question? We have something about whether it’s too late to start being a data scientist. (58:30)

Alexey: No, I don’t think it’s late. As I said before, AI is just a tool you use; it doesn’t replace you. If you want to become a data scientist now, it’s actually the best time ever. Previously, you had to learn so much just to get started. Now, you can ask tools like ChatGPT to help you. You just need to learn how to use it effectively. (58:47)

Alexey: However, you should keep market conditions in mind. It’s difficult to be a junior right now because companies are very reluctant to hire juniors. It’s a bit odd because everyone wants seniors, but seniors get promoted, change jobs, or become self-employed. Someone needs to replace them, right? The population of seniors is dwindling, but companies still need fresh blood. In theory, the hiring pyramid should have a lot of juniors, fewer mid-level, even fewer seniors, and so on. But right now, that pyramid is a bit skewed. (58:47)

Johanna: Yeah. (1:00:24)

Alexey: But it’s improving. (1:00:26)

Johanna: Right. I think there’s only going to be more data in the future. So, it’s a good opportunity for people transitioning from other fields. (1:00:29)

Alexey: If you have an engineering background, becoming a data scientist is still a great idea. (1:00:49)

Johanna: Absolutely! (1:00:55)

Alexey: Having some academic background or expertise in areas that companies need can give you an edge. So, don’t be shy; just start! (1:00:56)

Book recommendations and personal reading experiences

Johanna: Cool! We’re almost at the hour, but there’s always the traditional last question: do you have a book recommendation for us or anything you’re reading at the moment? (1:01:10)

Alexey: Recommendation? Well, right now I’m reading The Boy in the Striped Pajamas. (1:01:20)

Johanna: Oh, it’s a bit heavy, isn’t it? (1:01:31)

Alexey: Yeah. I’m at the part where he found out about the people in uniforms, so it’s starting to get heavy. Reading is maybe an overstatement for me; it’s on my desk with a bookmark. Sometimes, I read it. I’m also reading a book about exercises for my back and lower body. When it comes to courses, I’m biased about recommending one community that does really cool courses. You should check it out! (1:01:37)

Johanna: I wonder which one that is! (1:02:30)

Alexey: Well, on that note, it was a pleasure! Do you have anything else we should mention? (1:02:41)

Johanna: I just want to thank you, Alexey. You’ve been a great help, and it makes my life so much easier. I can just check the questions before the interview, and it’s amazing. (1:02:51)

Alexey: Thanks! It’s always a pleasure. Now I have my chores ahead! So, thanks for joining, and I hope everyone enjoys this episode. (1:03:04)

Johanna: Thanks for having me! (1:03:17)

Subscribe to our weekly newsletter and join our Slack.
We'll keep you informed about our events, articles, courses, and everything else happening in the Club.

DataTalks.Club. Hosted on GitHub Pages. We use cookies.